1. Field of the Invention
The present invention relates to computerized simulation of hydrocarbon reservoirs in the earth which have been modeled as a three-dimensional grid of cells, and in particular to determination of reservoir attributes or properties on a cell-by-cell basis for the individual cells in the reservoir model.
2. Description of the Related Art
In the oil and gas industries, the development of underground hydrocarbon reservoirs typically includes development and analysis of computer simulation models. These underground hydrocarbon reservoirs are typically complex rock formations which contain both a petroleum fluid mixture and water. The reservoir fluid content usually exists in two or more fluid phases. The petroleum mixture in reservoir fluids is produced by wells drilled into and completed in these rock formations. Simulations of the nature and extent of the reservoir fluids is performed by what is known as reservoir simulation modeling. U.S. Pat. No. 7,526,418, which is owned by the assignee of the present application, is an example of reservoir simulation modeling.
The nature and extent of the rock formations in the reservoir also vary over the reservoir, and certain characteristics, known as properties or attributes, of the rock in the formations also vary. The attributes, and the nature and extent of the rock formations, are analyzed by what is known as geological modeling. Attributes such as water or oil saturation, porosity and permeability provided from the geological model are valuable in the planning and development of a reservoir.
Oil and gas companies have come to depend on geological models as an important tool to enhance the ability to exploit a petroleum reserve. Geological models of reservoirs and oil/gas fields have become increasingly large and complex.
The early development of compositional reservoir simulators in the industry was, so far as is known, restricted to reservoir models small enough to be characterized by a relatively small number of cells (of the order of 100,000) into which the reservoir of interest was organized.
The early models became too coarse in data content and accuracy for what have become known as giant oil and gas fields. Giant reservoirs are those mammoth subsurface reservoirs at various locations on the earth containing hydrocarbons and other fluids. Due to the reservoir size, the number of cells could be from one to several millions.
In addition, the increased accuracy of detailed seismic-data which samples the reservoir at 25-meter areal (x and y) intervals, has begun to demand models of hundreds of millions to billions of cells to assimilate all the available detail, which in turn has been intended to result in more accurate models of the reservoir and has lead to more effective and efficient reservoir performance.
There are a number of available computer implemented petrophysical modeling processes, also known in the art as petrophysical algorithms, which can be used to obtain measures of reservoir attributes based on data from formation core samples obtained from existing wells in the reservoir. Traditionally, such petrophysical algorithms were applied at the individual well location based on data obtained, from the well from the core samples. However, when characterizing and developing a reservoir field, a 3D geological model of the reservoir covering the entire 3D reservoir needs to be built to give accurate model for reservoir planning. The vast majority of model cells which do not lie at well locations have required some sort of interpolation technique to provide values of reservoir attributes for that vast majority of cells. The interpolation was applied between attribute values obtained from cell information at the locations of existing wells which had been calculated using conventional petrophysical algorithms. However, attributes of subsurface formation layers vary over the extent of the formation in the reservoir.
In the past when attempting to derive model attributes in the vast spaces over the reservoir where no well intersects, averaging methods from the few available data points have been applied. The interpolation or averaging method generally did not yield the accuracy as calculated from petrophysical algorithms. This technique thus suffered a lack of accuracy in attribute values when representing the usually complex structural nature of a reservoir. This is particularly the case where a giant reservoir is involved.
Essential reservoir properties like permeability are thus, so far as is known, currently calculated when building a geological model by using a few empirical functions or interpolated from those available locations, usually few, with actual well information. The geological model size usually ranges from tens of thousands for small reservoirs to hundreds of millions of cells for giant reservoirs. So far as is known, the current averaging or interpolation methods do not provide sufficient detail or accuracy in complex reservoirs.